Crop yield prediction plays a pivotal role in agricultural production. As the demand for farm products continues to rise, the issue of food security might worsen in the foreseeable future. Utilizing advanced technologies enables us to forecast yields for specific regions accurately and enhance management practices. Remote sensing empowers farmers to efficiently monitor various production aspects, such as crop growth dynamics and weather fluctuations.
Crop Yield Forecasting Advantages
Agriculture yield prediction is crucial for food producers as it enables them to accurately forecast harvests in specific fields for upcoming seasons. Historical data on crop development and its influencing factors, such as farming methods, quality of soil, climate and weather shifts, etc. are required for a comprehensive productivity assessment.
Crop yield estimation using remote sensing allows farmers to:
- make faster decisions on sowing, cultivation, harvesting, and stock transportation;
- determine the profitability of growing crops in specific regions;
- implement efficient farm techniques;
- streamline the use of available resources;
- enhance global food security;
- gain deeper insights into agricultural markets and potential trends.
Thus, yield estimation can make agricultural businesses sustainable and more efficient.
Factors Adversely Affecting Agricultural Crop Yields
Various factors badly affect plants’ development. Some are influenced by farm practices, and others are related to environmental conditions. In any case, the crop yield prediction dataset empowers farmers to ease the adverse effects of these factors on business. Let’s delve deeper into the three most critical types.
Environmental Factors
Such effects are environmental features that affect all organisms’ development. They are directly related to climatic changes.
Biotic Factors
This category encompasses the activities of beneficial organisms, pests, viruses, bacteria, and fungi, including their interactions and mutual influence on the environment. Climate changes directly affect organisms’ behavior, potentially stimulating bacterial growth while reducing plant productivity.
Climate change also affects the activity of pests and pathogens, exposing plants that have adapted to local issues to new biotic stresses. Moreover, pathogens might evolve in new environments, leading to new diseases or increased resistance in existing ones. Consequently, as climate change persists, the threat to crop production remains. In response, farmers can utilize tools for crop yield forecasts to enhance pest control measures.
Abiotic Factors
The abiotic factors pertain to the influence of the inorganic environment on plants and living organisms, leading to various types of shifts at physiological, morphological, molecular, and biochemical levels. Heat, cold, droughts, floods, reduced soil fertility, and soil salinity are all direct consequences of climatic changes.
Extreme weather events negatively impact planted crops and result in yield losses. This is primarily because growers tend to prioritize high-yielding plants over stress-resistant ones. Although global warming has several advantages (e.g., it accelerates plant maturity), overall, it remains an overwhelmingly negative phenomenon with a widespread impact on our planet’s living conditions. With the help of yield estimation, farmers can adjust agricultural operations, increasing crop productivity and minimizing environmental damage.
Technological Factors
Extensive farming methods remain popular in many countries. In particular, traditional tillage practices that harm topsoil, chemical fertilizers that disrupt the nutrient balance, and aggressive chemicals that endanger beneficial organisms are used. These practices can substantially decrease yields combined with factors like untimely planting, improper selection of planting areas, and inadequate disease and pest control. While fighting environmental challenges can be difficult, the choice of agricultural methods ultimately rests with farmers. Utilizing yield curve forecasts aids in picking optimal strategies.
Other Factors
Genetics plays a crucial role in determining the yield of particular crops, influencing productivity, stress resistance, and adaptability to changing conditions. Proper selection allows for healthy harvests while adhering to sustainable agriculture methods.
Additionally, when making agricultural decisions, it’s essential to consider socio-economic factors such as the farm’s location, local food demand from the population, and traditional farming practices prevalent in the region.
Crop Yield Prediction Challenges
Accurate crop yield prediction is vital for farmers, traders, and governments, especially in the face of challenges like global warming. At the same time, the results are influenced by several specific factors. They must be taken into account when analyzing to obtain the most accurate data. Let’s look at some of them:
- Clouds. Cloud-free skies are critical for clear satellite images of fields. However, farms are often placed in regions with rainy conditions, e.g., Great Britain, which makes satellite imagery difficult.
- Color. Farmers look for green areas on satellite images to assess the productivity of fields. Green areas can include fields with crops, lawns with grass, forests, or areas with other agricultural plants. This makes it difficult to screen out irrelevant green areas.
- Scale. The accuracy of yield estimation depends directly on the data scale. The assessment of factors affecting vegetation productivity should not be carried out within a single field but at a national or even international scale.
- Farm size. Agricultural land is non-uniform in terms of size and crops grown. To avoid errors in analysis, it is essential to be able to identify specific farms and separate fields with the crops under study.
- Phenology. In addition to the fact that many green areas are similar, it is not enough to simply separate crops from forests. Some crops, such as cassava and sugar, are also difficult to distinguish from each other on satellite images. To make the most accurate yield estimates, it is necessary to know which species are growing in each field.
The above challenges can make it difficult to identify fields with specific crops. However, determining them using images does not mean that farmers will be able to make a precise yield prediction instantly. For a comprehensive analysis, factors such as regional weather, plant conditions, and other aspects outlined in the previous chapter should be taken into account alongside the analyzed area.
Thanks to the development of satellite solutions, any farm can get an accurate yield forecast, regardless of the production scale and budget. This not only improves business profitability but also contributes to the development of sustainable agriculture.
